Search results for: capabilities approach

Authors: Adedayo Jeremiah Adeyekun, Samuel Oluwagbemiga Ishola

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This paper aimed to identify the significance of sustainability in the built environment, the economic and environmental importance to building and construction projects. Sustainability in the built environment has been a key objective of research over the past several decades. Sustainability in the built environment requires reconciliation between economic, environmental and social impacts of design and planning decisions made during the life cycle of a project from inception to termination. Planning for sustainability in the built environment needs us to go beyond our individual disciplines to consider the variety of economic, social and environmental impacts of our decisions in the long term. A decision to build a green residential development in an isolated location may pass some of the test of sustainability through its reduction in stormwater runoff, energy efficiency, and ecological sustainability in the building, but it may fail to be sustainable from a transportation perspective. Sustainability is important to the planning, design, construction, and preservation of the built environment; because it helps these activities reflect multiple values and considerations. In fact, the arts and sciences of the built environment have traditionally integrated values and fostered creative expression, capabilities that can and should lead the sustainability movement as society seeks ways to live in dynamic balance with its own diverse needs and the natural world. This research aimed to capture the state-of-the-art in the development of innovative sustainable design and planning strategies for building and construction projects. Therefore, there is a need for a holistic selection and implication approach for identifying potential sustainable strategies applicable to a particular project and evaluating the overall life cycle impact of each alternative by accounting for different applicable impacts and making the final selection among various viable alternatives.

Keywords: sustainability, built environment, planning, design, construction

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Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani

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This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.

Keywords: chaotic approach, phase space, Cao method, local linear approximation method

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Authors: Mounir Bekaik, Messaoud Ramdani

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We present in this work a new technique of stabilization for fault nonlinear systems. The approach we adopt focus on a fuzzy Luenverger observer. The T-S approximation of the nonlinear observer is based on fuzzy C-Means clustering algorithm to find local linear subsystems. The MOESP identification approach was applied to design an empirical model describing the subsystems state variables. The gain of the observer is given by the minimization of the estimation error through Lyapunov-krasovskii functional and LMI approach. We consider a three tank hydraulic system for an illustrative example.

Keywords: nonlinear system, fuzzy, faults, TS, Lyapunov-Krasovskii, observer

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Authors: Alessandro Marano

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Aim: The author describes the aesthetic modification using orthognathic surgery and closed rhinoplasty. Methods: Series of case study. After orthognathic surgery we can observe a dramatical change of aesthetic especially in the mid-face and nose projection. The advancement of maxillary bone through Le Fort I osteotomy will change the nasal tip projection and lips roundness; combining orthognathic surgery with closed approach rhinoplasty will manage both function and aesthetic of all mid face district. Results: Combining Le Fort I osteotomy with closed approach rhinoplasty resulted in good objective results with high patient satisfaction. Le Fort I osteotomy will increase projection of mid face and the closed approach rhinoplasty will modify the nasal shape to be more harmonic with the new maxillary district. The scars are not visible because hidden inside the mouth and nose. Conclusions: The orthognathic surgery combined with closed approach rhinoplasty are very effective for changing the aesthetic of the mid face. The results illustrate the difference between the use of orthognathic surgery only and to use it in association of closed approach rhinoplasty. Using both will allow to obtain a long lasting and pleasing results.

Keywords: orthognathic, rhinoplasty, aesthetic, face

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Authors: Vijayan Narayananayar

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Identifying learning gaps is crucial in ensuring learners have the necessary knowledge and skills to succeed. The Learning and Teaching (L&T) approach requires tutors to identify gaps in knowledge and improvise learning activities to close them. One approach to identifying learning gaps is through diagnostic assessment, which uses well-structured questions and answer options. The paper focuses on the use of diagnostic assessment as a learning and teaching approach in a foundational module at a polytechnic. The study used diagnostic assessment over two semesters, including the COVID and post-COVID semesters, to identify gaps in learning. The design of the diagnostic activity, pedagogical intervention, and survey responses completed by learners were analyzed. Results showed that diagnostic assessment can be an effective tool for identifying learning gaps and designing interventions to address them. Additionally, the use of diagnostic assessment provides an opportunity for tutors to engage with learners on a one-to-one basis, tailoring teaching to individual needs. The paper also discusses the design of diagnostic questions and answer options, including characteristics that need to be considered in achieving the target of identifying learning gaps. The implications of using diagnostic assessment as a learning and teaching approach include bridging the gap between theory and practice, and ensuring learners are equipped with skills necessary for their future careers. This paper can be useful in helping educators and practitioners to incorporate diagnostic assessment into their L&T approach.

Keywords: assessment, learning & teaching, diagnostic assessment, analytics

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Authors: Nilanthi Ratnayake, Wen-Ling Liu

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Prior research indicates an increasing gap between the skills and capabilities of graduates in the contemporary workplace across the globe. The challenge of addressing this issue primarily lies on the hands of higher education institutes/universities. In particular, surveys of UK employers and retailers found that soft skills including communication, numeracy, teamwork, confidence, analytical ability, digital/IT skills, business sense, language, and social skills are highly valued by graduate employers, and in achieving this, there are various assessed and non-assessed learning exercises have already been embedded into the university curriculum. To this end, this research study aims to explore the reflections of postgraduate student participation in a live commercial project (i.e. designing an advertising campaign for open days, summer school etc.) implemented with the intention of offering a transformative experience by deploying this project. Qualitative research methodology has been followed in this study, collecting data from three types of target audiences; students, academics and employers via a series of personal interviews and focus group discussions. Recorded data were transcribed, entered into NVIVO, and analysed using meaning condensation and content analysis. Students reported that they had a very positive impact towards improving self-efficacy, especially in relation to soft skills and confidence in seeking employment opportunities. In addition, this project has reduced cultural barriers for international students in general communications. Academic staff and potential employers who attended on the presentation day expressed their gratitude for offering a lifelong experience for students, and indeed believed that these type of projects contribute significantly to enhance skills and capabilities of students to cater the demands of employers. In essence, key findings demonstrate that an integration of knowledge-based skills into a live commercial project facilitate individuals to make the transition from education to employment in terms of skills, abilities and work behaviours more effectively in comparison to some other activities/assuagements that are currently in place in higher education institutions/universities.

Keywords: soft skills, commercially live project, higher education, student participation

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Authors: Kwaku Damoah

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The agricultural sector is characterized by continuous transformation, driven by factors such as demographic shifts, evolving consumer preferences, climate change, and migration trends. This dynamic environment presents complex challenges for key stakeholders including farmers, governments, and investors, who must navigate these changes to achieve optimal investment returns. To effectively predict market trends and uncover promising investment opportunities, a systematic, data-driven approach is essential. This paper introduces the Structural Evolution Index (SEI), a machine learning-based methodology. SEI is specifically designed to analyse long-term trends and forecast the potential of emerging agricultural products for investment. Versatile in application, it evaluates various agricultural metrics such as production, yield, trade, land use, and consumption, providing a comprehensive view of the evolution within agricultural markets. By harnessing data from the UN Food and Agricultural Organisation (FAOSTAT), this study demonstrates the SEI's capabilities through Comparative Exploratory Analysis and evaluation of international trade in agricultural products, focusing on Malaysia and Singapore. The SEI methodology reveals intricate patterns and transitions within the agricultural sector, enabling stakeholders to strategically identify and capitalize on emerging markets. This predictive framework is a powerful tool for decision-makers, offering crucial insights that help anticipate market shifts and align investments with anticipated returns.

Keywords: agricultural investment, algorithm, comparative exploratory analytics, machine learning, market trends, predictive analytics, structural evolution index

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Authors: Khaled M. Alhawiti

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Natural Language Processing (NLP) is an effective approach for bringing improvement in educational setting. This involves initiating the process of learning through the natural acquisition in the educational systems. It is based on following effective approaches for providing the solution for various problems and issues in education. Natural Language Processing provides solution in a variety of different fields associated with the social and cultural context of language learning. It is based on involving various tools and techniques such as grammar, syntax, and structure of text. It is effective approach for teachers, students, authors, and educators for providing assistance for writing, analysis, and assessment procedure. Natural Language Processing is widely integrated in the large number of educational contexts such as research, science, linguistics, e-learning, evaluations system, and various other educational settings such as schools, higher education system, and universities. Natural Language Processing is based on applying scientific approach in the educational settings. In the educational settings, NLP is an effective approach to ensure that students can learn easily in the same way as they acquired language in the natural settings.

Keywords: natural language processing, education, application, e-learning, scientific studies, educational system

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Authors: Ouzayr Rabhi, Ibtissam Arrassen

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To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

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Authors: Nuno Biga

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Continuous processes’ improvement is a permanent challenge for managers of any organization. Lean management means that efficiency gains can be obtained through a systematic framework able to explore synergies between processes, eliminate waste of time, and other resources. Leaderships in organizations determine the efficiency of the teams through their influence on collaborators, their motivation, and consolidation of ownership (group) feeling. The “organization health” depends on the leadership style, which is directly influenced by the intrinsic characteristics of each personality and leadership ability (leadership competencies). Therefore, it’s important that managers can correct in advance any deviation from expected leadership exercises. Top management teams must assume themselves as regulatory agents of leadership within the organization, ensuring monitoring of actions and the alignment of managers in accordance with the humanist standards anchored in a visible Code of Ethics and Conduct. This article is built around an innovative model of “Business Interactive Games” (BI GAMES) that simulates a real-life management environment. It shows that the strategic management of operations depends on a complex set of endogenous and exogenous variables to the intervening agents that require specific skills and a set of critical processes to monitor. BI GAMES are designed for each management reality and have already been applied successfully in several contexts over the last five years comprising the educational and enterprise ones. Results from these experiences are used to demonstrate how serious games in working living labs contributed to improve the organizational environment by focusing on the evaluation of players’ (agents’) skills, empower its capabilities, and the critical factors that create value in each context. The implementation of the BI GAMES simulator highlights that leadership skills are decisive for the performance of teams, regardless of the sector of activity and the specificities of each organization whose operation is intended to simulate. The players in the BI GAMES can be managers or employees of different roles in the organization or students in the learning context. They interact with each other and are asked to decide/make choices in the presence of several options for the follow-up operation, for example, when the costs and benefits are not fully known but depend on the actions of external parties (e.g., subcontracted enterprises and actions of regulatory bodies). Each team must evaluate resources used/needed in each operation, identify bottlenecks in the system of operations, assess the performance of the system through a set of key performance indicators, and set a coherent strategy to improve efficiency. Through the gamification and the serious games approach, organizational managers will be able to confront the scientific approach in strategic decision-making versus their real-life approach based on experiences undertaken. Considering that each BI GAME’s team has a leader (chosen by draw), the performance of this player has a direct impact on the results obtained. Leadership skills are thus put to the test during the simulation of the functioning of each organization, allowing conclusions to be drawn at the end of the simulation, including its discussion amongst participants.

Keywords: business interactive games, gamification, management empowerment skills, simulation living labs

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

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In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

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Authors: Mary Fargher

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This paper examines the opportunities of using a more hierarchical approach to geospatial enquiry in using GIS in school geography. A case is made that it is not just the lack of teacher technological knowledge that is stopping some teachers from using GIS in the classroom but that there is a gap in their understanding of how to link GIS use more specifically to the pedagogy of teaching geography with GIS. Using a hierarchical approach to geospatial enquiry as a theoretical framework, the analysis shows clearly how concepts of spatial distribution, interaction, relation, comparison, and temporal relationships can be used by teachers more explicitly to capitalise on the analytical power of GIS and to construct what can be interpreted as powerful geographical knowledge. An exemplar illustrating this approach on the topic of geo-hazards is then presented for critical analysis and discussion. Recommendations are then made for a model of progression for geography teacher education with GIS through hierarchical geospatial enquiry that takes into account beginner, intermediate, and more advanced users.

Keywords: digital geography, GIS, education, hierarchical geospatial enquiry, powerful geographical knowledge

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Authors: Anurag Jain, Rajneesh Kumar

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Cloud computing is the outcome of rapid growth of internet. Due to elastic nature of cloud computing and unpredictable behavior of user, load balancing is the major issue in cloud computing paradigm. An efficient load balancing technique can improve the performance in terms of efficient resource utilization and higher customer satisfaction. Load balancing can be implemented through task scheduling, resource allocation and task migration. Various parameters to analyze the performance of load balancing approach are response time, cost, data processing time and throughput. This paper demonstrates a two level load balancer approach by combining join idle queue and join shortest queue approach. Authors have used cloud analyst simulator to test proposed two level load balancer approach. The results are analyzed and compared with the existing algorithms and as observed, proposed work is one step ahead of existing techniques.

Keywords: cloud analyst, cloud computing, join idle queue, join shortest queue, load balancing, task scheduling

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Authors: Robert Roznowski

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The thought process of the character is never more evident than when singing alone onstage. The composer scores the emotional state and the lyricist voices the inner conflict as the character shares with an audience her or his deepest feelings. It is at these moments that a character may be thought of as voicing her or his inner monologue. Using examples from several musical theatre songs, this presentation will look at a codified approach to analyze a song from a more psychological perspective. Using the clues from the score, traditional character analysis and a psychological-based scoring method an actor may explore more fully inhabit and express the sung and unsung thoughts of the character. The approach yields a richer and more complex approach to acting the song.

Keywords: acting, analysis, musical theatre, psychology

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Authors: Prakash Singh, Thembinkosi Twalo

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The sustainability of the Buffalo City Metropolitan Municipality (BCMM), in South Africa, is being threatened by the reported cases of poor administration, weak management of resources, inappropriate job performance, and inappropriate job behaviour of some of the workers. Since the structural-functionalists assume that formal education is a solution to societal challenges, it therefore means that the BCMM should not be experiencing this threat since many of its workers have various levels of formal education. Consequently, this study using the mixed method research approach, set out to investigate the paradoxical co-existence of inappropriate job behaviour and performance with formal education at the BCMM. Considering the impact of human factors in the labour process, this study draws attention to the divergent objectives of skill and skill bearer, with the application of knowledge subject to the knowledge bearer’s motives, will, attitudes, ethics and values. Consequently, inappropriate job behaviour and performance practices could be due to numerous factors such as lack of the necessary capabilities or refusal to apply what has been learnt due to racial or other prejudices. The role of the human factor in the labour process is a serious omission in human capital theory, which regards schooling as the only factor contributing to the ability to do a job. For this reason this study’s theoretical framework is an amalgamation of the four theories - human capital, social capital, cultural capital, and reputation capital – in an effort to obtain a broader view of the factors that shape job behaviour and performance. Since it has been established that human nature plays a crucial role in how workers undertake their responsibilities, it is important that this be taken into consideration in the BCMM’s monitoring and evaluation of the workers’ job performance practices. Hence, this exploratory study brings to the fore, the effects of poor job performance practices on the job satisfaction of workers.

Keywords: human capital, poor job performance practices, service delivery, workers’ job satisfaction

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Authors: M. Moyzykh, I. Klichuk, L. Sabirov, D. Kolomentseva, E. Magommedov

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Modern city electrical grids are forced to increase their density due to the increasing number of customers and requirements for reliability and resiliency. However, progress in this direction is often limited by the capabilities of existing network equipment. New energy sources or grid connections increase the level of short-circuit currents in the adjacent network, which can exceed the maximum rating of equipment–breaking capacity of circuit breakers, thermal and dynamic current withstand qualities of disconnectors, cables, and transformers. Superconducting fault current limiter (SFCL) is a modern solution designed to deal with the increasing fault current levels in power grids. The key feature of this device is its instant (less than 2 ms) limitation of the current level due to the nature of the superconductor. In 2019 Moscow utilities installed SuperOx SFCL in the city power grid to test the capabilities of this novel technology. The SFCL became the first SFCL in the Russian energy system and is currently the most powerful SFCL in the world. Modern SFCL uses second-generation high-temperature superconductor (2G HTS). Despite its name, HTS still requires low temperatures of liquid nitrogen for operation. As a result, Moscow SFCL is built with a cryogenic system to provide cooling to the superconductor. The cryogenic system consists of three cryostats that contain a superconductor part and are filled with liquid nitrogen (three phases), three cryocoolers, one water chiller, three cryopumps, and pressure builders. All these components are controlled by an automatic control system. SFCL has been continuously operating on the city grid for over three years. During that period of operation, numerous faults occurred, including cryocooler failure, chiller failure, pump failure, and others (like a cryogenic system power outage). All these faults were eliminated without an SFCL shut down due to the specially designed cryogenic system backups and quick responses of grid operator utilities and the SuperOx crew. The paper will describe in detail the results of SFCL operation and cryogenic system maintenance and what measures were taken to solve and prevent similar faults in the future.

Keywords: superconductivity, current limiter, SFCL, HTS, utilities, cryogenics

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Apollinaire Barme, Simon Tamayo, Arthur Gaudron

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This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e- commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.

Keywords: e-commerce, statistical modeling, regression, empirical research

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Authors: Denis Spirjakin, Alexander Baranov, Saba Akbari, Natalia Kalenova, Vladimir Sleptsov

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In this paper we propose the approach to power management in wireless combustible gas sensors. This approach makes possible drastically prolong sensor nodes autonomous lifetime. That is necessary to tie battery replacement to every year technical service procedures which are claimed by safety standards. Using this approach the current consumption of the wireless combustible gas sensor node was decreased from 80 mA to less than 2 mA and the power consumption from more than 220 mW to 4.6 mW. These values provide autonomous lifetime of the node more than one year.

Keywords: Gas sensors, power management, wireless sensor network

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Authors: F. M. Pisano, M. Ciminello

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Aerospace, mechanical, and civil engineering infrastructures can take advantages from damage detection and identification strategies in terms of maintenance cost reduction and operational life improvements, as well for safety scopes. The challenge is to detect so called “barely visible impact damage” (BVID), due to low/medium energy impacts, that can progressively compromise the structure integrity. The occurrence of any local change in material properties, that can degrade the structure performance, is to be monitored using so called Structural Health Monitoring (SHM) systems, in charge of comparing the structure states before and after damage occurs. SHM seeks for any "anomalous" response collected by means of sensor networks and then analyzed using appropriate algorithms. Independently of the specific analysis approach adopted for structural damage detection and localization, textual reports, tables and graphs describing possible outlier coordinates and damage severity are usually provided as artifacts to be elaborated for information extraction about the current health conditions of the structure under investigation. Visual Analytics can support the processing of monitored measurements offering data navigation and exploration tools leveraging the native human capabilities of understanding images faster than texts and tables. Herein, a SHM system enrichment by integration of a Visual Analytics component is investigated. Analytical dashboards have been created by combining worksheets, so that a useful Visual Analytics tool is provided to structural analysts for exploring the structure health conditions examined by a Principal Component Analysis based algorithm.

Keywords: interactive dashboards, optical fibers, structural health monitoring, visual analytics

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Authors: Artsiom Zinchanka

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The world faces now one of the largest migration crisis and the European Union meets challenges in accepting the flow of migrants that could not be handled finally at this step. This crisis is complicated with many factors, such as military conflict in the Middle East; absence of the appropriate conditions in the refugees’ camps; but also with the complicity of the migration flow consisting of the Sub-Saharan migrants. This type of migrants leave their homelands for many reasons including poverty, not appropriate level of social and economic conditions, absence of infrastructure and access to the education and medical care. In practice, when the restrictive approach directed to limit the flow of illicit migration and to send illicit migrants back to their homelands is not always working, the approach directed to the root causes of the migration crisis can be more effective in settling the crisis. The Cotonou Agreement and the following treaties concluded between the European Union, and Sub-Saharan states show that the European Union considers the development of human rights and appropriate social and economic conditions in the Sub-Saharan states as one of the most important factors addressing the migration crisis. The preventive approach as the efforts of the European Union to develop appropriate social and economic conditions in Sub-Saharan states is considered in this article, as well as its evolution and current condition. This article also considers pros and cons of this approach and the obstacles that this approach faces. The research methods include review of literature and documents, analytical and descriptive methods.

Keywords: migration crisis, preventive approach, Sub-Saharan States, the European Union

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Authors: Govindaraj Ramanathan

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The time delay and the structural stability are major issues in big size projects due to several factors. Improper planning and poor coordination lead to delay in construction, which sometimes result in reworking or rebuilding. This definitely increases the cost and time of project. This situation stresses the structural engineers to plan out of the limits of contemporary technology utilizing non-chronological approach with creative ideas. One of the strategies to solve this issue is through structural integrity solutions in a cost-effective way. We have faced several problems in a project worth 470 million USD, and one such issue is crane girder installation with composite steel beams. We have applied structural integrity approach with the proper and revised planning schedule to solve the problem efficiently with minimal expenses.

Keywords: construction management, delay, non-chronological approach, composite beam, structural integrity

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Authors: J. H. Park, S. K. Lee, Y. W. Kim, D. C. Ko

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A large variety of pipe flange is required in marine and construction industry.Pipe flanges are usually welded or screwed to the pipe end and are connected with bolts.This approach is very simple and widely used for a long time, however, it results in high development cost and low productivity, and the productions made by this approach usually have safety problem at the welding area.In this research, a new approach of forming pipe flange based on cold forging and floating die concept is presented.This innovative approach increases the effectiveness of the material usage and save the time cost compared with conventional welding method. To ensure the dimensional accuracy of the final product, the finite element analysis (FEA) was carried out to simulate the process of cold forging, and the orthogonal experiment methods were used to investigate the influence of four manufacturing factors (pin die angle, pipe flange angle, rpm, pin die distance from clamp jig) and predicted the best combination of them. The manufacturing factors were obtained by numerical and experimental studies and it shows that the approach is very useful and effective for the forming of pipe flange, and can be widely used later.

Keywords: cold forging, FEA (finite element analysis), forge-3D, rotating forming, tubes

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Authors: Taye O. Famuditi, Jonathan Potts, Malcolm Bray

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This paper examines the shoreline management planning policy in England and its suitability for ameliorating the diverse environmental problems associated with Nigeria’s coastal zones. It examines the success of SMPs in England since the mid-1990s and progress achieved, with the aim of understudying the current management approach that can be transferred to Nigeria to strengthen its adoption, and as a necessary corollary, implementation of the SMPs. This paper also examines key elements of the shoreline management frameworks in England and provides answers to the question: Would shoreline management planning approach in England be appropriate and feasible in Nigeria? It further concludes that many of the action plans and principles of participation should be adoptable provided that a participatory approach that involves all stakeholders including community members and relevant sectorial ministries as well as appropriate legal framework is encouraged.

Keywords: shoreline management plans, coastal zone management, stakeholder engagement, participatory approach, Nigeria

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Authors: Kien Vu, Jien Min Soh, Mohamed Jahangir Abubacker, Piyawut Pattamanon, Soojin Lee, Suvro Banerjee

Abstract:

Recent advances in Generative Artificial Intelligence (GenAI), in particular Large Language Models (LLMs) have shown promise to disrupt multiple industries at scale. However, LLMs also present unique challenges, notably, these so-called "hallucination" which is the generation of outputs that are not grounded in the input data that hinders its adoption into production. Common practice to mitigate hallucination problem is utilizing Retrieval Agmented Generation (RAG) system to ground LLMs'response to ground truth. RAG converts the grounding documents into embeddings, retrieve the relevant parts with vector similarity between user's query and documents, then generates a response that is not only based on its pre-trained knowledge but also on the specific information from the retrieved documents. However, the RAG system is not suitable for tabular data and subsequent data analysis tasks due to multiple reasons such as information loss, data format, and retrieval mechanism. In this study, we have explored a novel methodology that combines planning-and-execution and code generation agents to enhance LLMs' data analysis capabilities. The approach enables LLMs to autonomously dissect a complex analytical task into simpler sub-tasks and requirements, then convert them into executable segments of code. In the final step, it generates the complete response from output of the executed code. When deployed beta version on DataSense, the property insight tool of PropertyGuru, the approach yielded promising results, as it was able to provide market insights and data visualization needs with high accuracy and extensive coverage by abstracting the complexities for real-estate agents and developers from non-programming background. In essence, the methodology not only refines the analytical process but also serves as a strategic tool for real estate professionals, aiding in market understanding and enhancement without the need for programming skills. The implication extends beyond immediate analytics, paving the way for a new era in the real estate industry characterized by efficiency and advanced data utilization.

Keywords: large language model, reasoning, planning and execution, code generation, natural language processing, prompt engineering, data analysis, real estate, data sense, PropertyGuru

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Authors: Annika Schmidt, Ausama Hadi Ahmed, Carlo Menon

Abstract:

End effectors for robotic systems are becoming more and more advanced, resulting in a growing variety of gripping tasks. However, most grippers are application specific. This paper presents a gripper that interacts with an object’s surface rather than being dependent on a defined shape or size. For this purpose, ingressive and astrictive features are combined to achieve the desired gripping capabilities. The developed prototype is tested on a variety of surfaces with different hardness and roughness properties. The results show that the gripping mechanism works on all of the tested surfaces. The influence of the material properties on the amount of the supported load is also studied and the efficiency is discussed.

Keywords: claw, dry adhesion, insects, material properties

Procedia PDF Downloads 359

Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

Abstract:

The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

Procedia PDF Downloads 639

Authors: Ankita Singh

Abstract:

Sex trafficking and child pornography are those kinds of borderless crimes which can not be effectively prevented only through the laws and efforts of one country because it requires a proper and smooth collaboration among countries. Eradication of international human trafficking syndicates, criminalisation of international cyber offenders, and effective ban on child pornography is not possible without applying effective universal laws; hence, continuous collaboration of all countries is much needed to adopt and routinely update these universal laws. Congregation of countries on an international platform is very necessary from time to time, where they can simultaneously adopt international agendas and create powerful universal laws to prevent sex trafficking and child pornography in this modern digital era. In the past, some international steps have been taken through The Convention on the Rights of the Child (CRC) and through The Optional Protocol to the Convention on the Rights of the Child on the Sale of Children, Child Prostitution, and Child Pornography, but in reality, these measures are quite weak and are not capable in effectively protecting children from sexual abuse in this modern & highly advanced digital era. The uncontrolled growth of artificial intelligence (AI) and its misuse, lack of proper legal jurisdiction over foreign child abusers and difficulties in their extradition, improper control over international trade of digital child pornographic content, etc., are some prominent issues which can only be controlled through some new, effective and powerful universal laws. Due to a lack of effective international standards and a lack of improper collaboration among countries, Indian laws are also not capable of taking effective actions against child abusers. This research will be conducted through both doctrinal as well as empirical methods. Various literary sources will be examined, and a questionnaire survey will be conducted to analyse the effectiveness of international standards and Indian laws against child pornography. Participants in this survey will be Indian University students. In this work, the existing international norms made for protecting children from sexual abuse will be critically analysed. It will explore why effective and strong collaboration between countries is required in modern times. It will be analysed whether existing international steps are enough to protect children from getting trafficked or being subjected to pornography, and if these steps are not found to be sufficient enough, then suggestions will be given on how international standards and protections can be made more effective and powerful in this digital era. The approach of India towards the existing international standards, the Indian laws to protect children from being subjected to pornography, and the contributions & capabilities of India in strengthening the international standards will also be analysed.

Keywords: child pornography, prevention of children from sexual offences act, the optional protocol to the convention on the rights of the child on the sale of children, child prostitution and child pornography, the convention on the rights of the child

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Authors: Anduela Lile

Abstract:

The purpose of this cross sectional study was to investigate the effectiveness of teaching and learning Statistics from a student centered perspective in higher education institutions. Statistics education has emphasized the application of tangible and interesting examples in order to motivate students learning about statistical concepts. Participants in this study were 112 bachelor students enrolled in the ‘Applied Statistics’ course in Sports University of Tirana. Experimental group students received a student-centered teaching approach; Control group students received an instructor-centered teaching approach. This study found student-centered approach student group had statistically significantly higher assessments scores (52.1 ± 18.9) at the end of the evaluation compared to instructor-centered approach student group (61.8 ± 16.4), (t (108) = 2.848, p = 0.005). Results concluded that student-centered perspective can improve student positive attitude to statistical methods and to motivate project work. Therefore, findings of this study may be very useful to the higher education institutions to establish their learning strategies especially for courses related to Statistics.

Keywords: student-centered, instructor-centered, course assessment, learning outcomes, applied statistics

Procedia PDF Downloads 281